Artificial intelligence is a consortium of data-driven
methodologies which includes artificial neural networks, genetic
algorithms, fuzzy logic, probabilistic belief networks and machine
learning as its components. We have witnessed a phenomenal impact
of this data-driven consortium of methodologies in many areas of
studies, the economic and financial fields being of no exception.
In particular, this volume of collected works will give examples of
its impact on the field of economics and finance. This volume is
the result of the selection of high-quality papers presented at a
special session entitled 'Applications of Artificial Intelligence
in Economics and Finance' at the '2003 International Conference on
Artificial Intelligence' (IC-AI '03) held at the Monte Carlo
Resort, Las Vegas, Nevada, USA, June 23-26 2003. The special
session, organised by Jane Binner, Graham Kendall and Shu-Heng
Chen, was presented in order to draw attention to the tremendous
diversity and richness of the applications of artificial
intelligence to problems in Economics and Finance. This volume
should appeal to economists interested in adopting an
interdisciplinary approach to the study of economic problems,
computer scientists who are looking for potential applications of
artificial intelligence and practitioners who are looking for new
perspectives on how to build models for everyday operations.
There are still many important Artificial Intelligence disciplines
yet to be covered. Among them are the methodologies of independent
component analysis, reinforcement learning, inductive logical
programming, classifier systems and Bayesian networks, not to
mention many ongoing and highly fascinating hybridsystems. A way to
make up for their omission is to visit this subject again later. We
certainly hope that we can do so in the near future with another
volume of 'Applications of Artificial Intelligence in Economics and
Finance'.
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